Recent advances in deep reinforcement learning (dRL) now allow us to study several aspects of human-robot collaboration (HRC) in real-time. Overall, dRL has been applied to many different robotic applications such as mobile platforms [1]}, [2]}, robotic arm control [3]}, [4]}, robotic grasping [5]}, [6]}, humanoid robots [7]}, [8]}, drones [9]}, [10]}, quadruples [11]} and others. The success of the dRL in different robot environments lies in the ability of the dRL policies to learn motions and behaviours that, due to their complexity, are extremely difficult to be generated by hard-coded control laws.
